Perimenopausal depression （PMD） is an affective disorder that occurs in women during the transition from sexual maturity to old age. It can induce various complications， such as insomnia and cognitive decline. The etiology of PMD is complex. Although multiple hypotheses have been proposed， there is still no unified theory that fully explains its pathogenesis. Research into its mechanisms relies heavily on animal experiments， and establishing reliable animal models is crucial for experimental studies. Appropriate animal models can better simulate human pathophysiological states， rapidly evaluate the efficacy and safety of drugs and intervention methods， grasp the essence of the disease， and uncover its intrinsic connections， thereby exploring more advanced intervention strategies. However， there is a lack of systematic review and summarization of literature related to model construction. Additionally， traditional Chinese medicine （TCM）， adhering to the principles of ''syndrome differentiation and treatment'' and ''holistic concept''， has shown significant efficacy in treating PMD. In recent years， research exploring and analyzing its therapeutic mechanisms has been increasing. Therefore， to gain a clearer and more comprehensive understanding of PMD animal modeling methods and the mechanisms of TCM， this paper reviewed Chinese and English literature on PMD animal models and mechanisms of TCM in PMD treatment. It summarized the construction methods of single-factor and multi-factor PMD models， and discussed the advantages and disadvantages of each modeling approach. Furthermore， it delved into the mechanisms of TCM intervention in PMD， revealing that TCM formulas primarily exert their effects by regulating the hypothalamic-pituitary-adrenal axis， hypothalamic-pituitary-ovarian axis， gut-brain axis， cell signaling pathways， neural circuits， hormone levels， and neurotransmitter levels. This review aims to provide a reference for future research in this field. In summary， by summarizing the progress in the methods for PMD animal model construction and the mechanisms of TCM， the paper seeks to offer new insights into the mechanistic research of TCM intervention in PMD.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

OBJECTIVE To investigate the therapeutic effect and mechanism of Qiwei dongqingye powder （QDP） on bronchial asthma in mice. METHODS The mice were divided into blank group （normal saline）， model group （normal saline）， dexamethasone group （2 mg/kg）， and QDP low-， medium-， and high-dose groups （200， 400， 800 mg/kg）， with 14 mice in each group. Except for the blank group， mice in all other groups were given ovalbumin via intraperitoneal injection followed by aerosol inhalation to induce a bronchial asthma model. During the modeling process， mice in each group were administered corresponding drug solutions or normal saline intragastrically/intraperitoneally. After the last medication， the number of cells in the bronchoalveolar lavage fluid （BALF） of the mice was observed and counted； the pathological changes of the bronchus and lung tissue were observed； the levels of malondialdehyde （MDA）， nitric oxide （NO）， total superoxide dismutase （T-SOD）， and glutathione peroxidase （GSH-Px） in the lung tissue of the mice were determined， and the level of interleukin-17 （IL-17） in the BALF and serum was determined. Transcriptomics was employed to predict and validate the mechanism of action of QDP against bronchial asthma. RESULTS Compared with the model group， the total cell count， neutrophil count， lymphocyte count， and macrophage counts in the BALF of the QDP high-dose group were all significantly reduced （ P ＜0.05）； the levels of MDA and NO in the lung tissue， and the levels of IL-17 in the BALF and serum were all decreased significantly （ P ＜0.05）； the levels of T-SOD and GSH-Px were significantly increased （ P ＜0.05）； the arrangement of lung tissue cells tended to normalize， with reduced infiltration of inflammatory cells and decreased exfoliation of bronchial simple columnar epithelial cells. The transcriptomic results revealed that the differentially expressed genes were B-cell receptor signaling pathway， nuclear factor κB （NF-κB） signaling pathway， ferroptosis signaling pathway， and others. Further validation revealed that， compared with the model group， the expression levels of NF-κB p65 and chemokine ligand 20， as well as the phosphorylation level of NF-κB inhibitor protein α， were significantly decreased in the lung tissues of the mice in all QDP groups （ P ＜0.05）. Conversely， the protein expression of nuclear factor erythroid 2-related factor 2 （Nrf2） and heme oxygenase 1 （HO-1） were significantly increased （ P ＜0.05）. CONCLUSIONS QDP can effectively alleviate bronchial asthma by inhibiting the NF-κB signaling pathway， activating the Nrf2/HO-1 signaling pathway， regulating oxidative stress， and reducing inflammatory responses.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

China has become the country with the highest global burden of heart failure(HF).Despite the widespread use of prognostic-improving medications today,the mortality rate of HF remains high,reaching 13.7％at one year-particularly among patients with heart failure with reduced ejection fraction(HFrEF).HF interventional device therapy(structural intervention)targets the structural factors underlying HF,including atrial pressure,ventricular remodeling,and valvular intervention.It leverages the heart's intrinsic physiological properties and pathological progression mechanisms to deliver treatments through interventions without external active forces,achieving anatomical or functional repair.This field has emerged as a rapidly growing area and plays an increasingly critical role in HF management.This article provides a comprehensive review and summary of the latest advancements in HF and cardiomyopathy interventional therapy over the past year.It covers various novel technologies and products currently in the research phase,aiming to provide an in-depth analysis of the current status and future directions of HF interventional therapy,and further advance the development of this discipline.

Treatment-resistant depression(TRD)is a severe psychiatric disorder with a high incidence bringing heavy burden of disease,and better treatment options still need to be explored.In recent years,the antidepressant effects of nitrous oxide(N2O)and its application in TRD have attracted attention.N2O exerts unique rapid onset of action and has comparative advantages in terms of adverse reactions and tolerability and may become a new therapeutic drug for TRD.N2O may exert effects through mechanisms such as antagonizing N-methyl-D-aspartate(NMDA)receptors,regulating serotonin and dopamine,brain-derived neurotrophic factor(BDNF)signaling pathways,and the opioid receptor system.In clinical studies,the efficacy and safety of N2O for TRD have shown promise,displaying advantageous characteristics compared to existing therapies,and the limitations of N2O,such as its side effects,can often be improved via modification of the therapeutic regimen.Future research will mainly focus on validating the long-term efficacy and safety of standardized N2O treatment regimens through larger sample clinical trials,as well as further exploring its individualized or comprehensive treatment,and in-depth neurobiological mechanisms,in order to provide new choices and optimization strategies for clinical treatment practices suitable for relevant populations.

The working principle of Bausch&Lomb BL11110 phacoemulsification system was described.Three cases of typical faults of the phacoemulsification system were introduced,and the causes were analyzed,then the maintenance measures were given accordingly.References were provided for diagnosing and eliminating the faults of the phacoemulsification system.[Chinese Medical Equipment Journal,2025,46(4):118-120]

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

The xylitol dehydrogenase(XDH)is a crucial enzyme involved in the xylose utilization in pentose-catabolizing yeasts and fungi.In addition to producing xylulose,XDH can also be employed to develop a biosensor for monitoring xylitol concentration.In this study,the gene encoding the thermophilic fungus Talaromyces emersonii XDH(TeXDH)was heterologously expressed in Escherichia coli BL21(DE3)at 16 ℃ in the soluble form.Recombinant TeXDH with high purity was purified by using a Ni-NTA affinity column.Size-exclusion chromatography and SDS-PAGE analysis demonstrated that the puri-fied recombinant TeXDH exists as a native trimer with a molecular mass of approximately 116 kD,and is composed of three identical subunits,each with a molecular weight of around 39 kD.The TeXDH strictly preferred NAD+as a coenzyme to NADP+.The optimal temperature and pH of the TeXDH were 40 ℃and 10.0,respectively.After EDTA treatment,the enzyme activity of TeXDH decreased to 43.26％of the initial enzyme activity,while the divalent metal ions Mg2+or Ca2+could recover the enzyme activity of TeXDH,reaching 103.32％and 110.69％of the initial enzyme activity,respectively,making them the optimal divalent metal ion cofactors for TeXDH enzyme.However,the divalent metal ions of Mn2+,Ni2+,Cu2+,Zn2+,Co2+,and Cd2+significantly inhibited the activity of TeXDH.ICP-MS and molecular doc-king studies revealed that 1 mol/L of TeXDH bound 2 mol/L Zn2+ions and 1 mol/L Mg2+ion.Further-more,TeXDH exhibited a high specificity for xylitol,laying the foundation for the development of future xylitol biosensors.